Monolithic Spiropyran-Based Porous Polysilsesquioxanes with Stimulus-Responsive Properties
Bibliographic record
Abstract
Dynamic materials comprising spiropyrans have emerged as one of the most interesting and promising class of stimulus-responsive materials. Spiropyrans are often embedded in polymer matrices; their covalent attachment into porous monolithic silsesquioxane frameworks, however, is virtually unexplored. We demonstrate that a silylated spiropyran derivative can be covalently incorporated into ultralight silsesquioxane-based bulk materials by a two-step co-condensation sol-gel approach without restricting its conformational freedom and thus its stimulus-responsive properties. UV-vis measurements prove the conversion of the colorless closed-ring form of the spiropyran molecule into its highly colored purple isomer or the yellow colored protonated structure thereof. The transformation can be triggered simply by irradiation of the spiropyran-containing silsesquioxane monolith with UV or visible light or by the pH value of the chemical environment. A strong dependence of the surface polarity and water wettability on the prevalent isomer was observed. The contact angle of a water droplet on the monolithic surface can be altered from 146 to 100° by irradiation of the monolith with UV light for 3 min. Additionally, the prepared materials possess high specific surface areas, low bulk densities, and porosities of up to 84%.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".